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LatestXHTokenX2.5
XHTokenText / LLM

XHToken releases Spark-X2.5, a 4B open LLM

The Apache-2.0 instruction-tuned model targets developers who want a small, permissively licensed text generator.

Aug 24, 2026
UpdateApache 2.0
Spark-X2.5-4B

XHToken has published Spark-X2.5-4B, a four-billion-parameter instruction-tuned language model released under the permissive Apache-2.0 license. The model is available now on Hugging Face, where it is listed as a text-only, dense (non-MoE) system.

At 4B parameters, Spark-X2.5 sits in the increasingly crowded small-model tier, where compact instruction-tuned LLMs are prized for running on modest hardware, fine-tuning cheaply, and serving latency-sensitive applications. The Apache-2.0 terms are the notable detail here: they allow commercial use, modification, and redistribution with minimal friction, which matters to teams wary of the usage restrictions attached to some other open-weight releases.

What we know

  • Roughly 4B parameters, dense architecture
  • Instruction-tuned for chat and task following
  • Apache-2.0 license, text-only modality
  • Distributed via Hugging Face

The release record leaves several specifics unstated, including context length and benchmark results, so buyers will want to test the model against their own workloads before committing. As an initial entry in the Spark-X line, it establishes a baseline that future revisions can build on.

Why it matters: the value of a small model like this rests less on headline scores than on the combination of size and license. For developers who need a self-hostable, commercially usable 4B model, Spark-X2.5 is worth a look — and worth benchmarking carefully given how much the record leaves open.

Sources

  • XHToken/Spark-X2.5-4B

    Hugging Face

    Visit
OlderZhipu's GLM-5.3 Targets Coding at a Fraction of the CostZhipu AI · Text / LLM · 2 months agoNewerNVIDIA's PhoneLLM Targets Voice Agents on the LinePipecat Ai · Text / LLM · 2 months ago

Get the model

Hugging Face

Specs

Parameters4B
Context window1.0M tokens
Size8.2 GB
PrecisionBF16
ArchitectureSpark2_5ForCausalLM
LicenseAPACHE-2.0
Downloads38K
Likes1.4K

Can you run it?

Runs on a laptop — about 4.7 GB at 4-bit.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    10.4 GB
  • 8-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    6.6 GB
  • 4-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    4.7 GB
Your machine
GGUF builds
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text / LLM

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